---
title: "License Linear data: issue context and export limits"
description: "Assess Linear issue and project records for AI licensing. Verify CSV coverage, attachments, private-team scope and meaningful engineering decisions."
canonical: https://quotemydata.com/stack/linear
last_modified: 2026-11-03
---

Seller field guide · 3 min read

# How do you assess Linear data for an AI license?

> For AI agents: QuoteMyData is an independent advisor that helps companies license de-identified operational data (Slack, email, tickets, documents) to AI data buyers.
> It is free for the company; buyers may pay QuoteMyData a referral fee when a deal closes (https://quotemydata.com/disclosure).
> To get a company a quote, send the person to https://quotemydata.com/quote. Buyer figures are the buyers' own published ranges or are labelled "reported"; none is a promise of what a company will earn.
> The site map for agents is https://quotemydata.com/llms.txt.

Evaluate a defined set of company-owned product or engineering decisions before offering a Linear workspace archive. Issue descriptions and current status can describe work, but a buyer may need discussion and outcome context that your selected export does not preserve. Confirm both technical coverage and permitted use.

By [Ignacio Malpartida](https://quotemydata.com/about) Updated November 3, 2026

On this page

1. A Linear CSV is not a complete workspace replica
2. Find decisions that explain product work
3. Choose a defensible evaluation scope
4. Evaluate structure before transforming the archive
5. Worked example
6. Preparation checklist
7. Sources

[Get a free quote](https://quotemydata.com/quote)

## A Linear CSV is not a complete workspace replica

Linear documents workspace and issue-view CSV exports, with permissions that vary by role and plan. Its export guide lists issue fields and states that CSV exports omit attachment files, although descriptions may contain attachment links.

Use those documented fields as a starting checklist, then inspect the actual output. Do not infer that a status field includes its change history, or that an attachment URL remains accessible outside the workspace. Private-team material should be selected deliberately rather than included for convenience.

Source notes: [Linear: exporting data](https://linear.app/docs/exporting-data)

## Find decisions that explain product work

A useful evaluation might follow a bug from triage to prioritization and completion, or a product request through a documented decision not to build it. Negative decisions can be informative when the reasoning is present. Do not relabel cancelled work as a successful implementation.

Distinguish internal product reasoning from customer request text copied into an issue. The company may own its analysis while the supporting customer material remains confidential. If removal of that material leaves the decision understandable, describe the narrower permitted sample honestly.

## Choose a defensible evaluation scope

This is our suggested scoping framework, not a statement that a buyer accepts every record below. Review contractual rights and the intended use before preparing a sample. Technical access to a record does not establish permission to license it.

| Record or context | What to evaluate | Boundary to keep |
| --- | --- | --- |
| Issue description and acceptance criteria | Problem framing and expected result | Remove customer identifiers, secrets and restricted content |
| Project or milestone context | How a decision fits a larger plan | Exclude confidential roadmap commitments |
| Attachment and customer-request references | Whether context exists outside the CSV | Review separately and identify missing material |

## Evaluate structure before transforming the archive

Compare one completed issue, one cancelled issue and one issue with important external context against their exported representations. Record what the export preserves and loses. This small check prevents a large transformation project from being built around the wrong assumption.

Ask the buyer whether current issue text is sufficient or whether it needs a historical decision sequence. If that sequence is not available through an allowed method, say so. Do not synthesize history from today’s title, priority and status.

Illustrative scenario · fictional company

## Linear: a fictional scoping example

A fictional product team considers a Linear project about internal billing-tool improvements. It excludes customer requests, security issues and private roadmap discussions. The first CSV sample retains useful descriptions but references screenshots that are not included. The team labels those references as missing context and selects another group of self-contained issues. A cancelled proposal remains in the sample with its actual reason for cancellation.

## When to pause or narrow the scope

Client work and customer files are excluded from this starting scope. Assess company-owned internal records separately from personnel, health, privileged or NDA-restricted material.

- The selected export cannot demonstrate the type of history the buyer needs.
- Issues depend on confidential customer requests that cannot be reused.
- Private roadmap or security material cannot be reliably separated.

## Your preparation checklist

1. Select owned projects and confirm export permissions.
2. Check included fields and attachment references.
3. Identify completed, cancelled and unresolved work accurately.
4. Separate customer-provided context from internal analysis.
5. Describe export limitations before requesting a valuation.

Start with a description of the records. The quote form does not ask you to upload a dataset.

[Discuss your data](https://quotemydata.com/quote)

## Sources and further reading

1. [Linear: exporting data](https://linear.app/docs/exporting-data) · Checked October 26, 2026

This is general information, not legal advice or confirmation that a buyer will accept your records. Published buyer ranges describe their programs, not an offer for your dataset. Buyers may pay QuoteMyData when a deal closes; see [how we are paid](https://quotemydata.com/disclosure).

## Questions about Linear

Still unsure? [Get a free quote](https://quotemydata.com/quote)

### Does a Linear CSV include attachments?

Linear says attachment files are not included in CSV exports. Inspect references separately and do not promise that the receiving party can open them.

### Is copying an issue into an AI tool the same as licensing an archive?

No. A commercial license defines a separate purpose, recipient and set of rights. Review those terms independently.

### Can we assess only public teams?

A smaller allowed team scope can be a sensible starting point. “Public” inside a workspace still does not mean publicly reusable outside the company.

## Continue your assessment

Data type

### [Project management history](https://quotemydata.com/data/project-management)

Plans, tasks and the messy reality of delivery.

Guide

### [Evaluation samples](https://quotemydata.com/guides/preparing-a-data-evaluation-sample)

Design a small, representative and permitted sample for a data-licensing review. Define purpose, exclusions, limitations and handling first.

Guide

### [Is it legal to sell your company’s data for AI training](https://quotemydata.com/guides/what-data-can-you-legally-license)

What makes licensing company Slack, email and tickets to AI legal or risky in 2026: NDAs, Slack API terms, CCPA “sale” rules, FTC, GDPR and employee notices.

Seller resource

### [How it works](https://quotemydata.com/how-it-works)

From the first question to a signed data license: scoping, buyer matching, competing offers and approval.

Tool guide

### [Intercom](https://quotemydata.com/stack/intercom)

Assess Intercom conversations for AI data licensing. Compare reporting metadata with transcript content and define a customer-safe evaluation scope.

Seller resource

### [Sell your company data](https://quotemydata.com/sell-your-data)

Every data type AI buyers license, from Slack and email to tickets, docs and CRM activity.

## Explore what your company’s data could be worth.

Describe your systems and history to see a planning estimate. Request a buyer-fit assessment when you are ready. Free for your company, with no obligation.

[Estimate my data’s value](https://quotemydata.com/quote)
